Recognizing patterns within a set of data is important in many fields, including speech recognition, image processing, seismic data, etc. Some image processors collect image data and then pre-process the data to prepare it to be correlated to reference data. Other systems, like speech recognition, are real time where the input data is compared in real time to reference data to recognize patterns. Once the patterns are “recognized” or matched to a reference, the system may output the reference. For example, a speech recognition system may output equivalent text to the processed speech patterns. Other systems, like biological systems may use similar techniques to determine sequences in molecular strings like DNA.
In some systems, there is a need to find patterns that are imbedded in a continuous data stream. In non-aligned data streams there are some situations where patterns may be missed if only a single byte-by-byte comparison is implemented. The situation where patterns may be missed occurs when there is a repeated or nested repeating patterns in the input stream or the pattern to be detected. A RP containing the sequence that is being searched for is loaded into storage where each element of the sequence has a unique address. An address register is loaded with the address of the first element of the RP that is to be compared with the first element of the input pattern (IP). This address register is called a “pointer.” In the general case, a pointer may be loaded with an address that may be either incremented (increased) or decremented (decreased). The value of the element pointed to by the pointer is retrieved and compared with input elements (IEs) that are clocked or loaded into a comparator.
In pattern recognition, it is often desired to compare elements of an IP to many RPs. For example, it may be desired to compare an IP resulting from digitizing a finger print to a library of RPs (all finger prints on file). To do the job quickly, elements of each RP may be compared in parallel with elements in the IP. Each RP may have repeating substrings (short patterns) which are smaller patterns embedded within the RP. Since a library of RPs may be quite large, the processing required may be considerable. It would be desirable to have a way of reducing the amount of storage necessary to hold the RPs. If the amount of data used to represent the RPs could be reduced, it may also reduce the time necessary to load and unload the RPs. Parallel processing may also be used where each one of the RPs and the IP are loaded into separate processing units to determine matches.
Other pattern recognition processing in biological systems may require the comparison of an IP to a large number of stored RPs that have substrings that are repeated. Processing in small parallel processing units may be limited by the storage size required for the RPs. Portable, inexpensive processing systems for chemical analysis, biological analysis, etc. may also be limited by the amount of storage needed to quickly process large numbers of RPs with repeating substrings.
There is, therefore, a need for a method and an apparatus to reduce the amount of information necessary to store RPs with repeated substrings by compressing and encoding the data representing the RPs. There is also a need for a method and apparatus to read and decode the RPs so that elements of the RPs may be compared to elements in an IP to determine occurrences of the RP contained in the IP.